P.P. Chattopadhyay

On the formation of V-phase in mechanically alloyed AlSiMg–SiCp metal matrix composites with trace scandium additions

Abstract Present investigation concerns development of AlSiMg–SiC composite microstructure with trace addition of scandium in the form of master alloy powder utilizing mechanical alloying technique. Influence of Sc on the phase formation in the present alloy has been demonstrated by carrying out differential scanning calorimetry (DSC) of the ball milled and solution treated samples. Variation of Vickers hardness of the samples as a function of ageing time shows that presence of SiC and Sc may reasonably improve the mechanical properties of the age hardened alloy. Scanning electron micrographs (SEM) and transmission electron micrograph (TEM) of the bulk samples demonstrate the influence of ball milling on the morphology and distribution of the SiC particulates and the precipitate. The formation of V-phase as a stable precipitate during ageing has been identified and characterized by carrying out the selected area diffraction pattern (SADP) analysis.

Incorporation of prior knowledge in neural network model for continuous cooling of steel using genetic algorithm

Abstract Artificial neural network model is developed for the prediction of phase transformation of steel from austenite, and thus construction of the continuous cooling transformation (CCT) diagram. The model for prediction of transformation temperatures from steel composition is developed using data from published CCT diagrams. The trained network sometimes fails to predict the sequence of the phase transformation, contradicting the fundamentals of metallurgy. To avoid such limitations of data driven models and to make the models truthful and reasonable from metallurgical standpoint, prior knowledge is incorporated using genetic algorithm, through modifying the weights and biases of a trained neural network. The conventionally backpropagated multi-layered perceptron is modified from error minimization as well as knowledge incorporation point of view through formulation of the problem in both single and multi-objective optimization domains. The predictions of six transformation temperatures by the new models are found to be significantly better than the conventionally trained model.

DETERMINATION OF MS TEMPERATURE IN COPPER-BEARING MICROALLOYED STEEL BY THE ANN TECHNIQUE

Abstract The recent study concerns the prediction of MS temperature in copper-bearing microalloyed steel. An attempt has been made to determine the role of Cu and microalloying elements (Ti and B) on the MS temperature individually as well as in combination. For this purpose, a suitable network has been designed for this particular system from the point of view of its predictive ability. Several networks with different learning algorithms and varying numbers of nodes and hidden layers were trained. A committee of four models which were found to yield lower training and testing error, has been created. The mean of the prediction of the committee members is used for validation of their prediction from the metallurgical point of view. The effects of different alloying/microalloying elements on the MS temperature as predicted by the ANN model has been interpreted in terms of the available metallurgical knowledge. La présente étude traite de la prédiction de la température Ms de l’acier cuprifère micro-allié. On a essayé de déterminer le rôle, individuel ainsi qu’en combinaison, du Cu et des éléments de microalliage (Ti et B) sur la température Ms. Dans ce but, on a conçu un réseau approprié à ce système particulier quant à son habileté de prévision. On a entraîné plusieurs réseaux ayant différents algorithmes d’apprentissage et avec un nombre variable de noeuds et de couches cachées. On a créé un comité de quatre modèles qui produisaient la plus faible erreur d’entraînement et d’évaluation. On utilise la moyenne de prédiction des membres du comité pour la validation de leur prédiction du point de vue métallurgique. On a interprété l’effet des différents éléments d’alliage/de micro-alliage sur la température Ms telle que prédite par le modèle ANN, du point de vue de la connaissance métallurgique disponible.

Computational design and development of novel Al-Mg-Sc-Cr alloy

Purpose – The purpose of this paper is to design and develop precipitation hardened Al-Mg alloy imparting enhanced strength with acceptable ductility through minor addition of Sc and Cr by using multi-objective genetic algorithm-based searching. In earlier attempts of strengthening aluminum alloys, owing to the formation of Al3Sc and Al7Cr phase, addition of Sc and Cr have yielded attractive precipitation hardening, respectively. Both the Al-Sc and Al-Cr system are quench sensitive due to presence of a sloping solvus in their phase diagrams. It is also known that both the Al3Sc and Al7Cr phases nucleate directly from the supersaturated solid solution without formation of GP-zones or transient phases prior to the formation of the Al3Sc and Al7Cr. Sc also found to have beneficial effect on the corrosion property of such alloys. In view of the above, it is of interest to explore the possibility of enhancing the age hardening effect in Al-Mg alloy by addition of Sc and Cr. Design/methodology/approach – The pa...